1. ] Open Science Grid Ben Clifford University of Chicago benc@ci.uchicago.edu

2. ] 2 The Open Science Grid vision Transform processing and data intensive science through a cross-domain self-managed distributed cyber-infrastructure that brings together campus and community infrastructure and facilitating the needs of Virtual Organizations (VO) at all scales

3. ] 3 The Evolution of the OSG 1999200020012002200520032004200620072008 2009 PPDG GriPhyN iVDGL TrilliumGrid3 OSG (DOE) (DOE+NSF) (NSF) Campus, regional grids LHC Ops LHC construction, preparation LIGO operation LIGO preparation European Grid + Worldwide LHC Computing Grid DOE Science Grid (DOE)

4. Initial Grid driver: High Energy Physics Tier2 Centre ~1 TIPS Online System Offline Processor Farm ~20 TIPS CERN Computer Centre FermiLab ~4 TIPS France Regional Centre Italy Regional CentreGermany Regional Centre Institute Institute ~0.25TIPS Physicist workstations ~100 MBytes/sec ~622 Mbits/sec ~1 MBytes/sec There is a “bunch crossing” every 25 nsecs. There are 100 “triggers” per second Each triggered event is ~1 MByte in size Physicists work on analysis “channels”. Each institute will have ~10 physicists working on one or more channels; data for these channels should be cached by the institute server Physics data cache ~PBytes/sec ~622 Mbits/sec or Air Freight (deprecated) Tier2 Centre ~1 TIPS Caltech ~1 TIPS ~622 Mbits/sec Tier 0 Tier 1 Tier 2 Tier 4 1 TIPS is approximately 25,000 SpecInt95 equivalents Image courtesy Harvey Newman, Caltech 4

5. ] Kuhlman: Biology Designing proteins that fold into specific structures and bind target molecules Millions of simulations lead to the creation of a few proteins in the wet-lab Brought to OSG’s attention by local campus research computing group that was being overwhelmed Assistant Professor and a lab of 5 graduate students http://www.isgtw.org/?pid=1000507 One protein can fold in many ways. This computationally designed protein switches between a zinc finger structure and a coiled-coil structure, depending on its environment.

6. ] For each protein we design, we consume about 5,000 CPU hours across 10,000 jobs,” says Kuhlman. “Adding in the structure and atom design process, we’ve consumed about 250,000 CPU hours in total so far.” Designing proteins in the Kuhlman Lab

7. ● 1.6 * 10^8 CPU-hours/year, 5 CPU-hours/sec ● http://www.opensciencegrid.org/Usage_Stats

8. Example: UJ cluster can provide ~10k CPU-hours per week right now, planned 32k

9. ] What OSG would like... Involvement as users:  application users at UJ making use of other OSG resources – use UJ cluster and through that develop grid-scale applications  resource provision – other OSG users use space compute capacity here